Triple

T14556374
Position Surface form Disambiguated ID Type / Status
Subject Rennes railway station E341551 entity
Predicate connectsTo P845 FINISHED
Object Lorient E153357 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Lorient | Statement: [Rennes railway station, connectsTo, Lorient]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lorient
Context triple: [Rennes railway station, connectsTo, Lorient]
  • A. Lorient chosen
    Lorient is a port city in the Brittany region of northwestern France, known for its maritime heritage and annual Interceltic Festival.
  • B. Landerneau
    Landerneau is a historic town in the Finistère department of Brittany in northwestern France, known for its medieval architecture and distinctive inhabited bridge over the Élorn River.
  • C. Concarneau
    Concarneau is a coastal town and fishing port in Brittany, France, known for its walled medieval "Ville Close" and maritime heritage.
  • D. Libourne
    Libourne is a commune in southwestern France’s Gironde department, known as a wine-trading center and gateway to the Bordeaux wine region.
  • E. Roscoff
    Roscoff is a picturesque coastal town in Brittany, France, known for its historic port, thalassotherapy centers, and traditional onion-exporting heritage.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d822db9c8481908213ceb39585f792 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb2f1490881908673f429e5288c86 completed April 14, 2026, 9:34 p.m.
NED1 Entity disambiguation (via context triple) batch_69fde16830c0819090a97b073c8e642d completed May 8, 2026, 1:13 p.m.
Created at: April 10, 2026, 1:23 a.m.